Effects of infrared heaters on snow accumulation, snowmelt, and snow–atmosphere energy exchange were examined at Niwot Ridge, Colorado (CO) and compared to a naturally warmer, but otherwise similar subalpine site in the Valles Caldera National Preserve, New Mexico (NM). Observed snow accumulation was 30% lower on average and snow melted out 16 days earlier in the heated plots compared to the controls. Soil temperature during snowmelt was 3°C greater on average and soil moisture was 4% lower on average in heated plots compared to controls. In NM, snow accumulation was 23% lower, snow melted 23 days earlier, soil temperature was 0.6°C greater, and soil moisture was 13% lower on average relative to CO controls. In order to estimate differences in energy and mass balance fluxes at the snow–atmosphere interface in control versus warmer plots, the 1-D, physically based snowmelt model, SNOWPACK, was used. Model results indicated that heaters alter radiative, turbulent and mass fluxes by amounts comparable to the differences between CO and NM fluxes. The proportion of the energy flux associated with latent heat exchange during snowmelt was 9–27% of the total energy flux in heated models and 19–22% of NM models compared to 3–7% in control models. Thus, sublimation loss to the atmosphere was greater in both experimentally and naturally warmer cases relative to the control case. We conclude that IR heaters can provide alterations to the timing and magnitude of snow accumulation and snowmelt consistent with conditions observed at a warmer analog site and with climate and hydrology model projections. Impacts of IR heating on energy partitioning and sublimation should be considered when designing manipulations of the snowpack, as reductions in snowmelt water may alter biological or ecological processes.

Sub-canopy snow ablation rates were measured for three years at forested research plots in the Sierra Nevada, California with a network of 24 automated snow depth sensors and monthly snow density surveys. Snow ablation rates, in mm SWE day -1, specific to each depth sensor location were estimated as the seasonal maximum SWE divided by the number of days from peak SWE to snow disappearance. Estimates of sub-canopy direct beam solar irradiance and sky view factor (SVF θ) derived from hemispherical photographs were used to explain the spatial distribution of snow ablation rates. Cumulative direct beam irradiance during the observed snowmelt periods explained the most variability in snow ablation rates for the most cloud-free melt season (58% in 2008; 4 cloudy days; at 15 sensor locations snowmelt duration ranged from 39 days to 88 days and direct irradiance ranged from 96MJm -2 to 603MJm -2) and explained the least ablation variability for the cloudiest melt season of the study (29% in 2009; 23 cloudy days; at 12 sensor locations snowmelt duration ranged from 45 days to 79 days and direct irradiance ranged from 121MJm -2 to 410MJm -2). Conversely, sky view factor (SVF θ) explained the most variability in snow ablation rates under cloudier conditions (i.e. 87% in 2009) and the relationships were strongest when developed over the entire hemisphere (i.e. SVF 90°, which ranged from 0.17 to 0.31). Combined, the two metrics studied here (sub-canopy direct beam irradiance and SVF θ) may be used to explain much of the observed plot-scale variability in SWE ablation at finer time scales relevant to snow and hydrological model applications. © 2012 Elsevier B.V.

Whereas many independent methods are used to estimate snow water equivalent (SWE) and its spatial distribution and seasonal variability, a need exists for a systematic characterization of inter-model differences at annual, seasonal, and regional scales necessary to quantify the associated uncertainty in these datasets. This study conducts a multi-scale validation and comparison, based on Airborne Snow Observatory data, of five state-of-the-art SWE datasets in the Sierra Nevada, California, including three SWE datasets from retrospective models: an INiTial REConstruction model (REC-INT), an improved REConstruction model based on the ParBal energy balance model (REC-ParBal), and a Sierra Nevada SWE REConstruction with Data Assimilation (REC-DA), and two operational SWE datasets from the U.S. National Weather Service, including the Snow Data Assimilation System (SNODAS) and the National Water Model (NWM-SWE). The results show that REC-DA and REC-ParBal provide the two most accurate estimates of SWE in the snowmelt season, both with small positive biases. REC-DA provides the most accurate spatial distribution of SWE (R2 = 0.87, MAE = 66 mm, PBIAS = 8.3%) at the pixel scale, while REC-ParBal has the least basin-wide PBIAS (R2 = 0.79, MAE = 73 mm, PBIAS = 4.1%) in the snowmelt season. Moreover, REC-DA underestimates peak SWE by −5.8%, while REC-ParBal overestimates it by 7.5%, when compared with the measured peak SWE at snow pillow stations across the Sierra Nevada. The two operational SWE products—SNODAS and NWM-SWE—are less accurate. Furthermore, the inter-model comparison reveals a certain amount of disagreement in snow water storage across time and space between SWE datasets. This study advances our understanding of regional SWE uncertainties and provides critical insights to support future applications of these SWE data products and therefore has broad implications for water resources management and hydrological process studies.

Western US forest ecosystems and downstream water supplies are reliant on seasonal snowmelt. Complex feedbacks govern forest-snow interactions in which forests influence the distribution of snow and the timing of snowmelt but are also sensitive to snow water availability. Notwithstanding, few studies have investigated the influence of forest structure on snow distribution, snowmelt and soil moisture response. Using a multi-year record from co-located observations of snow depth and soil moisture, we evaluated the influence of forest-canopy position on snow accumulation and snow depth depletion, and associated controls on the timing of soil moisture response at Boulder Creek, Colorado, Jemez River Basin, New Mexico, and the Wolverton Basin, California. Forest-canopy controls on snow accumulation led to 12-42cm greater peak snow depths in open versus under-canopy positions. Differences in accumulation and melt across sites resulted in earlier snow disappearance in open positions at Jemez and earlier snow disappearance in under-canopy positions at Boulder and Wolverton sites. Irrespective of net snow accumulation, we found that peak annual soil moisture was nearly synchronous with the date of snow disappearance at all sites with an average deviation of 12, 3 and 22days at Jemez, Boulder and Wolverton sites, respectively. Interestingly, sites in the Sierra Nevada showed peak soil moisture prior to snow disappearance at both our intensive study site and the nearby snow telemetry stations. Our results imply that the duration of soil water stress may increase as regional warming or forest disturbance lead to earlier snow disappearance and soil moisture recession in subalpine forests.